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I am a newbie in data analysis. I wish to know how to boxplot multiple columns (x-axis = Points, Score, Weigh) in a single graph and make the y-axis as a standardized scale for comparison. I have tried and couldn't understand the code (Python+Pandas+Seaborn) for this. Help me out guys. The dataset for the same is as follows:

Cars Points Score Weigh 0 Mazda RX4 3.90 2.620 16.46 1 Mazda RX4 Wag 3.90 2.875 17.02 2 Datsun 710 3.85 2.320 18.61 3 Hornet 4 Drive 3.08 3.215 19.44 4 Hornet Sportabout 3.15 3.440 17.02 5 Valiant 2.76 3.460 20.22 6 Duster 360 3.21 3.570 15.84 7 Merc 240D 3.69 3.190 20.00 8 Merc 230 3.92 3.150 22.90 9 Merc 280 3.92 3.440 18.30 10 Merc 280C 3.92 3.440 18.90 11 Merc 450SE 3.07 4.070 17.40 12 Merc 450SL 3.07 3.730 17.60 13 Merc 450SLC 3.07 3.780 18.00 14 Cadillac Fleetwood 2.93 5.250 17.98 15 Lincoln Continental 3.00 5.424 17.82 16 Chrysler Imperial 3.23 5.345 17.42 17 Fiat 128 4.08 2.200 19.47 18 Honda Civic 4.93 1.615 18.52 19 Toyota Corolla 4.22 1.835 19.90 20 Toyota Corona 3.70 2.465 20.01 21 Dodge Challenger 2.76 3.520 16.87 22 AMC Javelin 3.15 3.435 17.30 23 Camaro Z28 3.73 3.840 15.41 24 Pontiac Firebird 3.08 3.845 17.05 25 Fiat X1-9 4.08 1.935 18.90 26 Porsche 914-2 4.43 2.140 16.70 27 Lotus Europa 3.77 1.513 16.90 28 Ford Pantera L 4.22 3.170 14.50 29 Ferrari Dino 3.62 2.770 15.50 30 Maserati Bora 3.54 3.570 14.60 31 Volvo 142E 4.11 2.780 18.60

My output should look something like: Output Boxplot Graph

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I have a pandas dataset with a toy version that can be created with this

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I created a function that returns a img tag with a dynamic src,

Everything works but I want to make it shorter :

Dirty version

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I have a dataframe as follows:

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What could I be missing?

Code to delete user using Azure AD B2C:

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I wrote an example with mtcars.

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I am trying to parse this complex JSON data into a Flutter application. I am able to get the JSON data successfully, but not able to display the data in the application. See the code and JSON data below. What I am doing wrong?

JSON Data

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I am trying to subsample a data.frame in a way that the sample would have observations that capture as much variation as possible among a set of columns of the original data.frame.

An example with the mtcars dataset: I'd like to find 3 cars that are the most different from each other by mpg, vs and carb. Looking at the data visually, it would probably be Toyota Corolla (high mpg, vs 1, low carb), Cadillac Fleetwood (low mpg, vs 0, medium carb) and either Maserati Bora (low-med mpg, vs 0, high carb) or Ferrari Dino (medium mpg, vs 0, med-high carb):

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I'm using "tiles" to show content, clicking on a tile expands content. Within the expanding content, I'm using the left hand side for displaying text (spec-info) and for the right hand side I'm using (icon-percent) to display an icon. I'm happy with this outcome as the icon sitting at the right hand side is positioned well in comparison to the text. However when on smaller device sizes, (ipad, iphone) - the "split" view of using left and right would be reverted to full width with the icon scaling appropriately and displaying above the text. I'm familiar with media queries but not sure they're appropriate for this implementation? any ideas would be really appreciated! I've created a working fiddle here too: https://jsfiddle.net/6gsvjt4r/1/

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